Journal Article10.1109/TAC.2011.2160593
Quantized Consensus by Means of Gossip Algorithm
Javad Lavaei,Richard M. Murray +1 more
152
TL;DR: This paper deals with the distributed averaging problem over a connected network of agents, subject to a quantization constraint, and shows that a quantized consensus is reached for an arbitrary quantizer by means of the stochastic gossip algorithm proposed in a recent paper.
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Abstract: This paper deals with the distributed averaging problem over a connected network of agents, subject to a quantization constraint It is assumed that at each time update, only a pair of agents can update their own states in terms of the quantized data being exchanged The agents are also required to communicate with one another in a stochastic fashion It is shown that a quantized consensus is reached for an arbitrary quantizer by means of the stochastic gossip algorithm proposed in a recent paper The expected value of the time at which a quantized consensus is reached is lower and upper bounded in terms of the topology of the graph for a uniform quantizer In particular, it is shown that these bounds are related to the principal submatrices of the weighted Laplacian matrix A convex optimization is also proposed to determine a set of probabilities used to pick a pair of agents that leads to a fast convergence of the gossip algorithm
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References
Consensus problems in networks of agents with switching topology and time-delays
TL;DR: A distinctive feature of this work is to address consensus problems for networks with directed information flow by establishing a direct connection between the algebraic connectivity of the network and the performance of a linear consensus protocol.
Consensus and Cooperation in Networked Multi-Agent Systems
Reza Olfati-Saber,J.A. Fax,Richard M. Murray +2 more
- 05 Mar 2007
TL;DR: A theoretical framework for analysis of consensus algorithms for multi-agent networked systems with an emphasis on the role of directed information flow, robustness to changes in network topology due to link/node failures, time-delays, and performance guarantees is provided.
Exploring complex networks
TL;DR: This work aims to understand how an enormous network of interacting dynamical systems — be they neurons, power stations or lasers — will behave collectively, given their individual dynamics and coupling architecture.
Coordination of groups of mobile autonomous agents using nearest neighbor rules
Ali Jadbabaie,Jie Lin,A.S. Morse +2 more
TL;DR: A theoretical explanation for the observed behavior of the Vicsek model, which proves to be a graphic example of a switched linear system which is stable, but for which there does not exist a common quadratic Lyapunov function.